HYDROSAFE:一种混合确定性-概率模型,用于生成合成设备配置文件
Abdelkareem Jaradat1, Muhamed Alarbi1, Anwar Haque1
1The Department of Computer Science, Western University, London, ON N6A 3K7, Canada.
Sensors (Basel, Switzerland)
|September 14, 2024
概括
水利安全能产生现实的合成电器功耗数据,解决现实世界数据集的稀缺问题. 这种混合型号通过精确的数据驱动洞察来增强智能家居能源管理系统.
科学领域:
- 能源系统 能源系统
- 数据科学数据科学数据科学
- 人工智能的人工智能
背景情况:
- 对于智能家居能源管理系统和算法来说,可靠的电力消耗数据至关重要.
- 现有的公开可用的数据集是有限的,且成本高昂.
- 需要有效的方法来生成高准确度的合成功耗数据.
研究的目的:
- 提出HYDROSAFE,一种新的混合确定性-概率模型,用于生成合成电器功耗配置文件.
- 为了解决收集真实世界电力消耗数据的稀缺性和耗时性质.
- 通过现实的合成数据,加强智能家居能源管理系统的开发.
主要方法:
- 采用中位数差异测试 (MDT) 来描述功耗配置文件.
- 基于利用密度和动态时间扭曲的设备操作模式 (DDTWSC) 的空间聚类,以聚类设备使用.
- 集成的随机元件 (白噪声,开关激增,波纹,边缘位置) 为增强的现实主义.
主要成果:
- 该HYDROSAFE模型成功生成了合成电器功耗配置文件.
- 使用规范化的DTW距离矩阵进行评估,证明了高保真度.
- 在1Hz采样频率下获得了10个样本的平均DTW距离,这表明真实数据的近似性.
结论:
- 液体安全有效地产生现实的合成电器功耗数据.
- 该模型的高保真性支持其在开发和测试智能家居能源管理系统中的应用.
- 这种方法为克服现场数据限制提供了可行的解决方案.
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